Learning Spatial Terms Without Explicit Negative Instances

TitleLearning Spatial Terms Without Explicit Negative Instances
Publication TypeTechnical Report
Year of Publication1990
AuthorsRegier, T.
Other Numbers621
Abstract

A method is presented for learning to associate scenes with spatial terms, in the absence of explicit negative instances, using error back-propagation. A straightforward approach, in the learning of a given term, is to take all positive instances for any other term to be implicit negative instances for the term in question. While this approach is inadequate, a variation on it is shown to work well: error signals from implicit negative instances are attenuated, so that an implicit negative instance will have less effect on the network's weights than will a positive instance of the same error magnitude. It is also shown that "a priori" knowledge of which pairs of spatial terms are antonyms facilitates the learning process.

URLhttp://www.icsi.berkeley.edu/pubs/techreports/tr-90-057.pdf
Bibliographic Notes

ICSI Technical Report TR-90-057

Abbreviated Authors

T. Regier

ICSI Publication Type

Technical Report